Prediction of miRNA-mRNA associations in Alzheimer’s disease mice using network topology

BMC Genomics

Hyemyung Seo¹  Soo Young Cho³  Young Seek Lee¹  Soojun Park²  Charny Park⁴  Haneul Noh¹ 

[1] Department of Molecular & Life Sciences, Hanyang University, 1271 Sa-dong, Sangrok-gu, Ansan, Gyeonggi-do, South Korea;Bio-Medical IT Convergence Research Department, ETRI, 218 Gajeong-ro, Yusoeng-gu, Daejeon 305-700, Korea;Laboratory of Developmental Biology and Genomics, College of Veterinary Medicine, Research Institute for Veterinary Science BK21, Program for Veterinary Science, Seoul National University, Seoul 151-742, Korea;Ewha Research Center for Systems Biology (ERCSB), Ewha Womans University, Seoul 120-750, Korea

关键词: Network module;    Transcriptome;    microRNA;    Alzheimer’s disease;   

Others  :  1216342
DOI  :  10.1186/1471-2164-15-644

 received in 2014-01-23, accepted in 2014-07-08,  发布年份 2014

【 摘 要 】

Background

Little is known about the relationship between miRNA and mRNA expression in Alzheimer’s disease (AD) at early- or late-symptomatic stages. Sequence-based target prediction algorithms and anti-correlation profiles have been applied to predict miRNA targets using omics data, but this approach often leads to false positive predictions. Here, we applied the joint profiling analysis of mRNA and miRNA expression levels to Tg6799 AD model mice at 4 and 8 months of age using a network topology-based method. We constructed gene regulatory networks and used the PageRank algorithm to predict significant interactions between miRNA and mRNA.

Results

In total, 8 cluster modules were predicted by the transcriptome data for co-expression networks of AD pathology. In total, 54 miRNAs were identified as being differentially expressed in AD. Among these, 50 significant miRNA-mRNA interactions were predicted by integrating sequence target prediction, expression analysis, and the PageRank algorithm. We identified a set of miRNA-mRNA interactions that were changed in the hippocampus of Tg6799 AD model mice. We determined the expression levels of several candidate genes and miRNA. For functional validation in primary cultured neurons from Tg6799 mice (MT) and littermate (LM) controls, the overexpression of ARRDC3 enhanced PPP1R3C expression. ARRDC3 overexpression showed the tendency to decrease the expression of miR139-5p and miR3470a in both LM and MT primary cells. Pathological environment created by Aβ treatment increased the gene expression of PPP1R3C and Sfpq but did not significantly alter the expression of miR139-5p or miR3470a. Aβ treatment increased the promoter activity of ARRDC3 gene in LM primary cells but not in MT primary cells.

Conclusions

Our results demonstrate AD-specific changes in the miRNA regulatory system as well as the relationship between the expression levels of miRNAs and their targets in the hippocampus of Tg6799 mice. These data help further our understanding of the function and mechanism of various miRNAs and their target genes in the molecular pathology of AD.

【 授权许可】

   
2014 Noh et al.; licensee BioMed Central Ltd.

【 图 表 】

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【 参考文献 】

• [1]Vickers JC, Dickson TC, Adlard PA, Saunders HL, King CE, McCormack G: The cause of neuronal degeneration in Alzheimer’s disease. Prog Neurobiol 2000, 60(2):139-165.
• [2]Gouras GK, Almeida CG, Takahashi RH: Intraneuronal Aβ accumulation and origin of plaques in Alzheimer’s disease. Neurobiol Aging 2005, 26(9):1235-1244.
• [3]Billingsley ML, Kincaid RL: Regulated phosphorylation and dephosphorylation of tau protein: effects on microtubule interaction, intracellular trafficking and neurodegeneration. Biochem J 1997, 323(Pt 3):577-591.
• [4]Schwab C, Hosokawa M, McGeer PL: Transgenic mice overexpressing amyloid beta protein are an incomplete model of Alzheimer disease. Exp Neurol 2004, 188(1):52-64.
• [5]Satoh J: Molecular network of microRNA targets in Alzheimer’s disease brains. Exp Neurol 2012, 235(2):436-446.
• [6]Breving K, Esquela-Kerscher A: The complexities of microRNA regulation: mirandering around the rules. Int J Biochem Cell Biol 2010, 42(8):1316-1329.
• [7]Oakley H, Cole SL, Logan S, Maus E, Shao P, Craft J, Guillozet-Bongaarts A, Ohno M, Disterhoft J, Van Eldik L, Berry R, Vassar R: Intraneuronal beta-amyloid aggregates, neurodegeneration, and neuron loss in transgenic mice with five familial Alzheimer’s disease mutations: potential factors in amyloid plaque formation. J Neurosci 2006, 26(40):10129-10140.
• [8]Vitvitsky VM, Garg SK, Keep RF, Albin RL, Banerjee R: Na + and K + ion imbalances in Alzheimer’s disease. Biochim Biophys Acta 2012, 1822(11):1671-1681.
• [9]Brewer GJ: Copper excess, zinc deficiency, and cognition loss in Alzheimer’s disease. Bio factors 2012, 38(2):107-113.
• [10]Bowman AB, Kwakye GF, Herrero Hernández E, Aschner M: Role of manganese in neurodegenerative diseases. J Trace Elem Med Biol 2011, 25(4):191-203.
• [11]Zatta P, Drago D, Bolognin S, Sensi SL: Alzheimer’s disease, metal ions and metal homeostatic therapy. Trends Pharmacol Sci 2009, 30(7):346-355.
• [12]Caccamo A, Majumder S, Richardson A, Strong R, Oddo S: Molecular interplay between mammalian target of rapamycin (mTOR), amyloid-beta, and Tau: effects on cognitive impairments. J Biol Chem 2010, 285(17):13107-13120.
• [13]Yang Y, Geldmacher DS, Herrup K: DNA replication precedes neuronal cell death in Alzheimer’s disease. J Neurosci 2001, 21(8):2661-2668.
• [14]Spires TL, Orne JD, SantaCruz K, Pitstick R, Carlson GA, Ashe KH, Hyman BT: Region-specific dissociation of neuronal loss and neurofibrillary pathology in a mouse model of tauopathy. Am J Pathol 2006, 168(5):1598-1607.
• [15]High FA, Zhang M, Proweller A, Tu L, Parmacek MS, Pear WS, Epstein JA: An essential role for Notch in neural crest during cardiovascular development and smooth muscle differentiation. J Clin Invest 2007, 117(2):353-363.
• [16]Woo HN, Park JS, Gwon AR, Arumugam TV, Jo DG: Alzheimer’s disease and Notch signaling. Biochem Biophys Res Commun 2009, 390(4):1093-1097.
• [17]Wanker EE: Hip1 and Hippi participate in a novel cell death-signaling pathway. Dev Cell 2002, 2(2):126-128.
• [18]Zovoilis A, Agbemenyah HY, Agis-Balboa RC, Stilling RM, Edbauer D, Rao P, Farinelli L, Delalle I, Schmitt A, Falkai P, Burkhardt S, Sanabenesi F, Fischer A: microRNA-34c is a novel target to treat dementias. EMBO J 2011, 30(20):4299-4308.
• [19]Gaughwin PM, Ciesla M, Lahiri N, Tabrizi SJ, Brundin P, Bjorkqvist M: Hsa-miR-34b is a plasma-stable microRNA that is elevated in pre-manifest Huntington’s disease. Hum Mol Genet 2011, 20(11):2225-2237.
• [20]Minones-Moyano E, Porta S, Escaramis G, Rabionet R, Iraola S, Kagerbauer B, Espinosa-Parrilla Y, Ferrer I, Estivill X, Marti E: MicroRNA profiling of Parkinson’s disease brains identifies early downregulation of miR-34b/c which modulate mitochondrial function. Hum Mol Genet 2011, 20(15):3067-3078.
• [21]Cogswell JP, Ward J, Taylor IA, Waters M, Shi Y, Cannon B, Kelnar K, Kemppainen J, Brown D, Chen C, Prinjha RK, Richardson JC, Saunders AM, Roses AD, Richards CA: Identification of miRNA changes in Alzheimer’s disease brain and CSF yields putative biomarkers and insights into disease pathways. J Alzheimers Dis 2008, 14(1):27-41.
• [22]Gomez-Nicola D, Fransen NL, Suzzi S, Perry VH: Regulation of microglial proliferation during chronic neurodegeneration. J Neurosci 2013, 33(6):2481-2493.
• [23]Conde JR, Streit WJ: Microglia in the aging brain. J Neuropathol Exp Neurol 2006, 65(3):199-203.
• [24]Liu N, Landreh M, Cao K, Abe M, Hendriks GJ, Kennerdell JR, Zhu Y, Wang LS, Bonini NM: The microRNA miR-34 modulates ageing and neurodegeneration in Drosophila. Nature 2012, 482(7386):519-523.
• [25]Hundhausen C, Misztela D, Berkhout TA, Broadway N, Saftig P, Reiss K, Hartmann D, Fahrenholz F, Postina R, Matthews V, Kallen KJ, Rose-John S, Ludwig A: The disintegrin-like metalloproteinase ADAM10 is involved in constitutive cleavage of CX3CL1 (fractalkine) and regulates CX3CL1-mediated cell-cell adhesion. Blood 2003, 102(4):1186-1195.
• [26]Yokota T: [MicroRNA and central nervous system]. Brain and Nerve / No to Shinkei 2009, 61(2):167-176.
• [27]Fiore R, Khudayberdiev S, Christensen M, Siegel G, Flavell SW, Kim TK, Greenberg ME, Schratt G: Mef2-mediated transcription of the miR379-410 cluster regulates activity-dependent dendritogenesis by fine-tuning Pumilio2 protein levels. EMBO J 2009, 28(6):697-710.
• [28]Kurose H: Galpha12 and Galpha13 as key regulatory mediator in signal transduction. Life Sci 2003, 74(2–3):155-161.
• [29]Podolska A, Kaczkowski B, Kamp Busk P, Sokilde R, Litman T, Fredholm M, Cirera S: MicroRNA expression profiling of the porcine developing brain. PLoS One 2011, 6(1):e14494.
• [30]Lu J, He ML, Wang L, Chen Y, Liu X, Dong Q, Chen YC, Peng Y, Yao KT, Kung HF, Li XP: MiR-26a inhibits cell growth and tumorigenesis of nasopharyngeal carcinoma through repression of EZH2. Cancer Res 2011, 71(1):225-233.
• [31]Draheim KM, Chen HB, Tao Q, Moore N, Roche M, Lyle S: ARRDC3 suppresses breast cancer progression by negatively regulating integrin beta4. Oncogene 2010, 29(36):5032-5047.
• [32]Patwari P, Chutkow WA, Cummings K, Verstraeten VL, Lammerding J, Schreiter ER, Lee RT: Thioredoxin-independent regulation of metabolism by the alpha-arrestin proteins. J Biol Chem 2009, 284(37):24996-25003.
• [33]Patwari P, Emilsson V, Schadt EE, Chutkow WA, Lee S, Marsili A, Zhang Y, Dobrin R, Cohen DE, Larsen PR, Zavacki AM, Fong LG, Young SG, Lee RT: The arrestin domain-containing 3 protein regulates body mass and energy expenditure. Cell Metab 2011, 14(5):671-683.
• [34]Ke YD, Dramiga J, Schutz U, Kril JJ, Ittner LM, Schroder H, Gotz J: Tau-mediated nuclear depletion and cytoplasmic accumulation of SFPQ in Alzheimer’s and Pick’s disease. PLoS One 2012, 7(4):e35678.
• [35]Shen GM, Zhang FL, Liu XL, Zhang JW: Hypoxia-inducible factor 1-mediated regulation of PPP1R3C promotes glycogen accumulation in human MCF-7 cells under hypoxia. FEBS Lett 2010, 584(20):4366-4372.
• [36]Sumanasekera C, Kelemen O, Beullens M, Aubol BE, Adams JA, Sunkara M, Morris A, Bollen M, Andreadis A, Stamm S: C6 pyridinium ceramide influences alternative pre-mRNA splicing by inhibiting protein phosphatase-1. Nucleic Acids Res 2012, 40(9):4025-4039.
• [37]Bychkov ER, Gurevich VV, Joyce JN, Benovic JL, Gurevich EV: Arrestins and two receptor kinases are upregulated in Parkinson’s disease with dementia. Neurobiol Aging 2008, 29(3):379-396.
• [38]Wood H: Alzheimer disease: Arrestin’ Alzheimer disease progression? [beta]-arrestin 2 is a potential therapeutic target. Nat Rev Neurol 2013, 9(2):60.
• [39]Thathiah A, Horre K, Snellinx A, Vandewyer E, Huang Y, Ciesielska M, De Kloe G, Munck S, De Strooper B: [beta]-arrestin 2 regulates A [beta] generation and [gamma]-secretase activity in Alzheimer’s disease. Nat Med 2013, 19(1):43-49.
• [40]Fardilha M, Esteves SL, Korrodi-Gregorio L, da Cruz-e Silva OA, da Cruz-e Silva FF: The physiological relevance of protein phosphatase 1 and its interacting proteins to health and disease. Curr Med Chem 2010, 17(33):3996-4017.
• [41]Gautier L, Cope L, Bolstad BM, Irizarry RA: affy–analysis of Affymetrix GeneChip data at the probe level. Bioinformatics 2004, 20(3):307-315.
• [42]Langmead B, Salzberg SL: Fast gapped-read alignment with Bowtie 2. Nat Methods 2012, 9(4):357-359.
• [43]Kozomara A, Griffiths-Jones S: miRBase: integrating microRNA annotation and deep-sequencing data. Nucleic Acids Res 2011, 39(Database issue):D152-D157.
• [44]Langfelder P, Horvath S: WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics 2008, 9:559.
• [45]da Huang W, Sherman BT, Lempicki RA: Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 2009, 4(1):44-57.
• [46]Betel D, Wilson M, Gabow A, Marks DS, Sander C: The microRNA.org resource: targets and expression. Nucleic Acids Res 2008, 36(Database issue):D149-D153.
• [47]Garcia DM, Baek D, Shin C, Bell GW, Grimson A, Bartel DP: Weak seed-pairing stability and high target-site abundance decrease the proficiency of lsy-6 and other microRNAs. Nat Struct Mol Biol 2011, 18(10):1139-1146.
• [48]Brin S, Page L: The anatomy of a large-scale hypertextual Web search engine. Comput Networks Isdn 1998, 30(1–7):107-117.
• [49]Seo H, Isacson O: Abnormal APP, cholinergic and cognitive function in Ts65Dn Down’s model mice. Exp Neurol 2005, 193(2):469-480.
• [50]Soung YH, Pruitt K, Chung J: Epigenetic silencing of ARRDC3 expression in basal-like breast cancer cells. Sci Rep 2014, 4:3846.